The present invention relates to image processing and, more particularly, to a method for performing automatic color constancy (CC) correction of real images and for video sequences without knowledge of either the color or the intensity of the illumination.
A colored object absorbs most of the spectrum of the illuminating light that falls on the surfaces of the object and reflects only a narrow range of the spectrum, which is interpreted as the color of the object. Thus, an object appears dark, unless there is a light source which includes unabsorbed colors (wavelengths). White light includes a wide range of the visible spectrum, thus, the reflected spectrum from a colored object illuminated by a white light, is considered as the physically “true spectrum” of the object. Arbitrary chromatic (colored) illumination, however, contains only a partial range of the spectrum, which leads to a distortion of the object's color. For example, a completely blue object appears blue under white illumination, since it reflects the blue part and absorbs the green and red parts of the white light that falls on it. On the other hand, the same object appears dark under red illumination, as the light, which falls on the surfaces of the objects, is absorbed completely.
Through a phenomenon called “color constancy” (CC), the visual system has an ability to partially correct the perceived color of an object so that the perceived color remains more constant than would be expected by the spectral composition of the light reflected from it under varying colored illumination. For example, a human observer identifies a similar of an observed object both at noon, when daylight is predominantly bluish, and at sunset, when daylight is predominantly reddish. “Color constancy” is explained by the observation that the perceived color of an object, depends both on the spectral composition of the light reflected from it, and on the spatial distribution of other colored objects in the field of view. The suggested operation of the visual system is such that each patch of color and its surrounding area causes a response or a set of responses in the visual system, which later translate into a specific perceived color. Human CC is not perfect, and it is regarded as a partial capability for discounting illumination chromaticity.
The human observer is unable to achieve color constancy in a photographed image merely by using his visual system, as if had he been present at the photographed scene. As suggested by Hedva Spitzer and Sarit Semo in an article titled “Color Constancy: A Biological Model and its Application for Still and Video Images, accepted for publication in a journal named Pattern Recognition, the contents of which are hereby incorporated by reference, this unableness is due to the small visual angle of the image within his entire visual field. Hence, although the image is observed by a human visual system, an algorithm that can correct it to appear naturally is still necessary. Known means in the prior art for achieving “color constancy”, i.e., partial correcting for departures from whiteness of the illuminating light, are described hereinbelow. Video cameras typically have manual means for achieving color constancy. These means require that the video camera be aimed manually at a reference surface that is assumed to be white under white illumination, to record parameters related to the spectrum of the illumination so that the subsequently recorded pictures may be corrected for the non-whiteness of the illumination. Furthermore, the illumination spectrum may change suddenly, for example, if a cloud passes in front of the sun, or if the object being photographed moves from sunlight to shade. These changes in illumination will affect the performance of the color constancy correction. More advanced video cameras often include automatic color constancy mechanisms, based on other principles such as color balancing by normalization, but these are not entirely satisfactory. Moreover, most of the prior art has an additional drawback that the problem of multiple sources of lighting is not solved.
U.S. Pat. No. 5,771,312, the contents of which are hereby incorporated by reference, discloses an advanced algorithm for partially correcting color images for colored illumination without knowledge of either the color or the intensity of the illumination. The algorithm takes into account the spatial distribution of other colored objects in the field of view, in a manner similar to that in which the neurons of the visual system process signals related to color vision to achieve color constancy. It was suggested that the retinal ganglion cells involved in color perception correspond to three kinds of cone cells that respond to color: red-processing cells, green-processing cells and blue-processing cells. On-center ganglion cells modify the cell response of chromatic light by subtracting surround responses from center responses. The mechanism is herein described: the on-center red-processing cells subtract green surround responses from red center responses, the on-center green-processing cells subtract red surround responses from green center responses and the on-center blue-processing cells subtract yellow surround responses from blue center responses. In addition, it is believed that at the ganglion cell level, the perception of color is further modified by responses from “remote” areas outside the receptive field that are even farther than the “surround” areas from the “center” areas. The algorithm imitates the above mechanisms of color perception to provide a partial color constancy correction for a color receptive field. However, the algorithm only has a limited capability for matching a perceived color of a patch presented in the center of a complex image with a reference patch presented on a neutral background. This limited capability is reflected in the inversion procedure which is used by the algorithm. Whereas in some embodiments of the above patent the surround area participates in the adaptation phase, the inversion phase does not take into account the surround area while translating the processed image into a perceived field level.
There is thus a widely recognized need for, and it would be highly advantageous to have, a more satisfactory method for performing color constancy correction, devoid of the above limitation.